CheckBlenAsymmetry
Xiang Ji
February 4, 2016
Load data from All.RData
rm(list=ls()) # clean up workspace
load("/Users/xji3/GitFolders/IGCCodonSimulation/All.RData")
paml.path <- "/Users/xji3/GitFolders/IGCCodonSimulation/"
IGC.geo.list <- c(3.0, 10.0, 50.0, 100.0, 500.0)
check.paml.path <- "/Users/xji3/TempChecking/IGCCodonSimulation/"
#IGC.geo.list <- c(3.0)
for (IGC.geo in IGC.geo.list){
for (localtree in 1:3){
summary_mat <- NULL
IGC.geo.path <- paste("IGCgeo_", toString(IGC.geo), ".0/", sep = "")
file.name <- paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "estimatedTau", "paml", "unrooted", "LocalTree", toString(localtree), "summary.txt", sep = "_")
for (sim.num in 0:(num.sim - 1)){
summary_file <- paste(check.paml.path, file.name, sep = "")
if (file.exists(summary_file)){
all <- readLines(summary_file, n = -1)
col.names <- strsplit(all[1], ' ')[[1]][-1]
row.names <- strsplit(all[length(all)], ' ')[[1]][-1]
summary_mat <- as.matrix(read.table(summary_file,
row.names = row.names,
col.names = col.names))
}
}
assign(paste("check_PAML", "estimatedTau", paste(toString(IGC.geo), ".0", sep = ""), "LocalTree", toString(localtree), "summary", sep = "_"), summary_mat)}
}
for (IGC.geo in IGC.geo.list){
for (localtree in 1:3){
summary_mat <- NULL
IGC.geo.path <- paste("IGCgeo_", toString(IGC.geo), ".0/", sep = "")
file.name <- paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "estimatedTau", "paml", "unrooted", "LocalTree", toString(localtree), "summary.txt", sep = "_")
for (sim.num in 0:(num.sim - 1)){
summary_file <- paste(paml.path, file.name, sep = "")
if (file.exists(summary_file)){
all <- readLines(summary_file, n = -1)
col.names <- strsplit(all[1], ' ')[[1]][-1]
row.names <- strsplit(all[length(all)], ' ')[[1]][-1]
summary_mat <- as.matrix(read.table(summary_file,
row.names = row.names,
col.names = col.names))
}
}
assign(paste("PAML", "estimatedTau", paste(toString(IGC.geo), ".0", sep = ""), "LocalTree", toString(localtree), "summary", sep = "_"), summary_mat)}
}
# Read in new PAML results
data.path <- paste(paralog, "",sep = "/")
for (IGC.geo in IGC.geo.list){
summary_mat <- NULL
IGC.geo.path <- paste("IGCgeo_", toString(IGC.geo), ".0/", sep = "")
file.name <- paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "estimatedTau", "paml", "unrooted", "1stTree", "summary.txt", sep = "_")
for (sim.num in 0:(num.sim - 1)){
summary_file <- paste(paml.path, file.name, sep = "")
if (file.exists(summary_file)){
all <- readLines(summary_file, n = -1)
col.names <- strsplit(all[1], ' ')[[1]][-1]
row.names <- strsplit(all[length(all)], ' ')[[1]][-1]
summary_mat <- as.matrix(read.table(summary_file,
row.names = row.names,
col.names = col.names))
}
}
assign(paste("PAML", "estimatedTau", paste(toString(IGC.geo), ".0", sep = ""), "1stTree", "summary", sep = "_"), summary_mat)
}
for (IGC.geo in IGC.geo.list){
summary_mat <- NULL
IGC.geo.path <- paste("IGCgeo_", toString(IGC.geo), ".0/", sep = "")
file.name <- paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "estimatedTau", "paml", "unrooted", "2ndTree", "summary.txt", sep = "_")
for (sim.num in 0:(num.sim - 1)){
summary_file <- paste(paml.path, file.name, sep = "")
if (file.exists(summary_file)){
all <- readLines(summary_file, n = -1)
col.names <- strsplit(all[1], ' ')[[1]][-1]
row.names <- strsplit(all[length(all)], ' ')[[1]][-1]
summary_mat <- as.matrix(read.table(summary_file,
row.names = row.names,
col.names = col.names))
}
}
assign(paste("PAML", "estimatedTau", paste(toString(IGC.geo), ".0", sep = ""), "2ndTree", "summary", sep = "_"), summary_mat)
}
# for (IGC.geo in IGC.geo.list){
# summary_mat <- NULL
# IGC.geo.path <- paste("IGCgeo_", toString(IGC.geo), ".0/", sep = "")
# file.name <- paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "10Tau", "paml", "unrooted", "1stTree", "summary.txt", sep = "_")
# for (sim.num in 0:(num.sim - 1)){
# summary_file <- paste(paml.path, file.name, sep = "")
# if (file.exists(summary_file)){
# all <- readLines(summary_file, n = -1)
# col.names <- strsplit(all[1], ' ')[[1]][-1]
# row.names <- strsplit(all[length(all)], ' ')[[1]][-1]
# summary_mat <- as.matrix(read.table(summary_file,
# row.names = row.names,
# col.names = col.names))
#
# }
# }
# assign(paste("PAML", "10Tau", paste(toString(IGC.geo), ".0", sep = ""), "1stTree", "summary", sep = "_"), summary_mat)
# }
#
# for (IGC.geo in IGC.geo.list){
# summary_mat <- NULL
# IGC.geo.path <- paste("IGCgeo_", toString(IGC.geo), ".0/", sep = "")
# file.name <- paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "10Tau", "paml", "unrooted", "2ndTree", "summary.txt", sep = "_")
# for (sim.num in 0:(num.sim - 1)){
# summary_file <- paste(paml.path, file.name, sep = "")
# if (file.exists(summary_file)){
# all <- readLines(summary_file, n = -1)
# col.names <- strsplit(all[1], ' ')[[1]][-1]
# row.names <- strsplit(all[length(all)], ' ')[[1]][-1]
# summary_mat <- as.matrix(read.table(summary_file,
# row.names = row.names,
# col.names = col.names))
#
# }
# }
# assign(paste("PAML", "10Tau", paste(toString(IGC.geo), ".0", sep = ""), "2ndTree", "summary", sep = "_"), summary_mat)
# }
#
# save.image("/Users/xji3/GitFolders/IGCCodonSimulation/All.RData")Feb 11 update
sum(PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_1_summary["ll",] < 0)## [1] 52sum(PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_2_summary["ll",] < 0)## [1] 59sum(PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_3_summary["ll",] < 0)## [1] 33hist((PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_1_summary["ll",])[PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_1_summary["ll",] < 0],
main = "lnL difference - local tree 1",
xlab = "lnL difference")
hist((PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_2_summary["ll",])[PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_2_summary["ll",] < 0],
main = "lnL difference - local tree 2",
xlab = "lnL difference")
hist((PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_3_summary["ll",])[PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_3_summary["ll",] < 0],
main = "lnL difference - local tree 3",
xlab = "lnL difference")
# OK, more check
sum(PAML_3.0_summary[4, ] < 5e-6 & PAML_3.0_summary[6, ] > 5e-6 )## [1] 29sum(PAML_3.0_summary[4, ] > 5e-6 & PAML_3.0_summary[6, ] < 5e-6 )## [1] 22# No asymmetry in the 0 branch length estimates
convert.summary <- function(localTree, summary, vector.names){
new.summary <- vector("numeric", length(vector.names))
names(new.summary) <- vector.names
if (localTree == 1){
new.summary[1:3] <- summary[1:3]
new.summary["N0_N6"] <- summary["N0_N5"]
new.summary["N0_kluyveriYDR418W"] <- summary["N0_kluyveriYDR418W"]
new.summary["N0_N1"] <- 0.0
new.summary["N1_N2"] <- summary["N0_N1"]
new.summary["N1_castelliiYDR418W"] <- summary["N0_castelliiYDR418W"]
new.summary["N2_bayanusYDR418W"] <- summary["N1_bayanusYDR418W"]
new.summary["N2_N3"] <- summary["N1_N2"]
new.summary["N3_N4"] <- summary["N2_N3"]
new.summary["N3_kudriavzeviiYDR418W"] <- summary["N2_kudriavzeviiYDR418W"]
new.summary["N4_N5"] <- summary["N3_N4"]
new.summary["N4_mikataeYDR418W"] <- summary["N3_mikataeYDR418W"]
new.summary["N5_paradoxusYDR418W"] <- summary["N4_paradoxusYDR418W"]
new.summary["N5_cerevisiaeYDR418W"] <- summary["N4_cerevisiaeYDR418W"]
new.summary["N6_N7"] <- summary["N5_N6"]
new.summary["N6_castelliiYEL054C"] <- summary["N5_castelliiYEL054C"]
new.summary["N7_N8"] <- summary["N6_N7"]
new.summary["N7_bayanusYEL054C"] <- summary["N6_bayanusYEL054C"]
new.summary["N8_N9"] <- summary["N7_N8"]
new.summary["N8_kudriavzeviiYEL054C"] <- summary["N7_kudriavzeviiYEL054C"]
new.summary["N9_mikataeYEL054C"] <- summary["N8_mikataeYEL054C"]
new.summary["N9_N10"] <- summary["N8_N9"]
new.summary["N10_paradoxusYEL054C"] <- summary["N9_paradoxusYEL054C"]
new.summary["N10_cerevisiaeYEL054C"] <- summary["N9_cerevisiaeYEL054C"]
}
else if (localTree == 2){
new.summary[1:3] <- summary[1:3]
new.summary["N0_N6"] <- 0.0
new.summary["N0_kluyveriYDR418W"] <- summary["N0_kluyveriYDR418W"]
new.summary["N0_N1"] <- summary["N0_N1"]
new.summary["N1_N2"] <- summary["N1_N2"]
new.summary["N1_castelliiYDR418W"] <- summary["N1_castelliiYDR418W"]
new.summary["N2_bayanusYDR418W"] <- summary["N2_bayanusYDR418W"]
new.summary["N2_N3"] <- summary["N2_N3"]
new.summary["N3_N4"] <- summary["N3_N4"]
new.summary["N3_kudriavzeviiYDR418W"] <- summary["N3_kudriavzeviiYDR418W"]
new.summary["N4_N5"] <- summary["N4_N5"]
new.summary["N4_mikataeYDR418W"] <- summary["N4_mikataeYDR418W"]
new.summary["N5_paradoxusYDR418W"] <- summary["N5_paradoxusYDR418W"]
new.summary["N5_cerevisiaeYDR418W"] <- summary["N5_cerevisiaeYDR418W"]
new.summary["N6_N7"] <- summary["N0_N6"]
new.summary["N6_castelliiYEL054C"] <- summary["N0_castelliiYEL054C"]
new.summary["N7_N8"] <- summary["N6_N7"]
new.summary["N7_bayanusYEL054C"] <- summary["N6_bayanusYEL054C"]
new.summary["N8_N9"] <- summary["N7_N8"]
new.summary["N8_kudriavzeviiYEL054C"] <- summary["N7_kudriavzeviiYEL054C"]
new.summary["N9_mikataeYEL054C"] <- summary["N8_mikataeYEL054C"]
new.summary["N9_N10"] <- summary["N8_N9"]
new.summary["N10_paradoxusYEL054C"] <- summary["N9_paradoxusYEL054C"]
new.summary["N10_cerevisiaeYEL054C"] <- summary["N9_cerevisiaeYEL054C"]
}
else if (localTree == 3){
new.summary[1:3] <- summary[1:3]
new.summary["N0_N6"] <- 0.0
new.summary["N0_kluyveriYDR418W"] <- summary["N0_kluyveriYDR418W"]
new.summary["N0_N1"] <- 0.0
new.summary["N1_N2"] <- summary["N0_N1"]
new.summary["N1_castelliiYDR418W"] <- summary["N0_castelliiYDR418W"]
new.summary["N2_bayanusYDR418W"] <- summary["N1_bayanusYDR418W"]
new.summary["N2_N3"] <- summary["N1_N2"]
new.summary["N3_N4"] <- summary["N2_N3"]
new.summary["N3_kudriavzeviiYDR418W"] <- summary["N2_kudriavzeviiYDR418W"]
new.summary["N4_N5"] <- summary["N3_N4"]
new.summary["N4_mikataeYDR418W"] <- summary["N3_mikataeYDR418W"]
new.summary["N5_paradoxusYDR418W"] <- summary["N4_paradoxusYDR418W"]
new.summary["N5_cerevisiaeYDR418W"] <- summary["N4_cerevisiaeYDR418W"]
new.summary["N6_N7"] <- summary["N0_N5"]
new.summary["N6_castelliiYEL054C"] <- summary["N0_castelliiYEL054C"]
new.summary["N7_N8"] <- summary["N5_N6"]
new.summary["N7_bayanusYEL054C"] <- summary["N5_bayanusYEL054C"]
new.summary["N8_N9"] <- summary["N6_N7"]
new.summary["N8_kudriavzeviiYEL054C"] <- summary["N6_kudriavzeviiYEL054C"]
new.summary["N9_mikataeYEL054C"] <- summary["N7_mikataeYEL054C"]
new.summary["N9_N10"] <- summary["N7_N8"]
new.summary["N10_paradoxusYEL054C"] <- summary["N8_paradoxusYEL054C"]
new.summary["N10_cerevisiaeYEL054C"] <- summary["N8_cerevisiaeYEL054C"]
}
else if (localTree == 4){
new.summary[vector.names] <- summary[vector.names]
}
return (new.summary)
}
for (IGC.geo in IGC.geo.list){
max.lnL.summary <- NULL
vector.names = rownames(get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = "")))
for (sim.num in 1:100){
max.pos <- which.max(c(get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_LocalTree_1_summary", sep = ""))["ll", sim.num],
get(paste("PAML_estimatedTau_",paste(toString(IGC.geo), ".0", sep = ""), "_LocalTree_2_summary", sep = ""))["ll", sim.num],
get(paste("PAML_estimatedTau_",paste(toString(IGC.geo), ".0", sep = ""), "_LocalTree_3_summary", sep = ""))["ll", sim.num],
get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = ""))["ll", sim.num]))
if (max.pos < 4){
new.summary <- convert.summary(max.pos, get(paste("PAML_estimatedTau", paste(toString(IGC.geo), ".0", sep = ""), "LocalTree", toString(max.pos), "summary", sep = "_"))[, sim.num], vector.names)
}
else{
new.summary <- get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = ""))[, sim.num]
}
max.lnL.summary <- cbind(max.lnL.summary, new.summary)
}
row.names(max.lnL.summary) <- row.names(get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = "")))
assign(paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "PAML", "maxlnL", "summary", sep = "_"), max.lnL.summary)
}
# Now check asymmetry again
# N4_N5
compare.mean.N4.N5.result <- matrix(c(mean(geo_3.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_3.0_PAML_maxlnL_summary["N9_N10",]),
mean(geo_3.0_PAML_maxlnL_summary["N4_N5",])/mean(geo_3.0_PAML_maxlnL_summary["N9_N10",]),
mean(PAML_estimatedTau_3.0_1stTree_summary["N4_N5", ]),
mean(PAML_estimatedTau_3.0_1stTree_summary["N9_N10", ]),
mean(PAML_estimatedTau_3.0_1stTree_summary["N4_N5", ])/mean(PAML_estimatedTau_3.0_1stTree_summary["N9_N10", ])),
2, 3, byrow = TRUE)
colnames(compare.mean.N4.N5.result) <- c("paralog1", "paralog2", "paralog1 / paralog2")
rownames(compare.mean.N4.N5.result) <- c("NEW", "old")
compare.sd.N4.N5.result <- matrix(c(sd(geo_3.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_3.0_PAML_maxlnL_summary["N9_N10",]),
sd(geo_3.0_PAML_maxlnL_summary["N4_N5",])/sd(geo_3.0_PAML_maxlnL_summary["N9_N10",]),
sd(PAML_estimatedTau_3.0_1stTree_summary["N4_N5", ]),
sd(PAML_estimatedTau_3.0_1stTree_summary["N9_N10", ]),
sd(PAML_estimatedTau_3.0_1stTree_summary["N4_N5", ])/sd(PAML_estimatedTau_3.0_1stTree_summary["N9_N10", ])),
2, 3, byrow = TRUE)
colnames(compare.sd.N4.N5.result) <- c("paralog1", "paralog2", "paralog1 / paralog2")
rownames(compare.sd.N4.N5.result) <- c("NEW", "old")
# N4_mikatae
compare.mean.N4.mikatae.result <- matrix(c(mean(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C",]),
mean(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W",])/mean(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C",]),
mean(PAML_estimatedTau_3.0_1stTree_summary["N4_mikataeYDR418W", ]),
mean(PAML_estimatedTau_3.0_1stTree_summary["N9_mikataeYEL054C", ]),
mean(PAML_estimatedTau_3.0_1stTree_summary["N4_mikataeYDR418W", ])/mean(PAML_estimatedTau_3.0_1stTree_summary["N9_mikataeYEL054C", ])),
2, 3, byrow = TRUE)
colnames(compare.mean.N4.mikatae.result) <- c("paralog1", "paralog2", "paralog1 / paralog2")
rownames(compare.mean.N4.mikatae.result) <- c("NEW", "old")
compare.sd.N4.mikatae.result <- matrix(c(sd(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C",]),
sd(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W",])/sd(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C",]),
sd(PAML_estimatedTau_3.0_1stTree_summary["N4_mikataeYDR418W", ]),
sd(PAML_estimatedTau_3.0_1stTree_summary["N9_mikataeYEL054C", ]),
sd(PAML_estimatedTau_3.0_1stTree_summary["N4_mikataeYDR418W", ])/sd(PAML_estimatedTau_3.0_1stTree_summary["N9_mikataeYEL054C", ])),
2, 3, byrow = TRUE)
colnames(compare.sd.N4.mikatae.result) <- c("paralog1", "paralog2", "paralog1 / paralog2")
rownames(compare.sd.N4.mikatae.result) <- c("NEW", "old")
compare.mean.N4.N5.result## paralog1 paralog2 paralog1 / paralog2
## NEW 0.03516 0.03868 0.909
## old 0.03516 0.03868 0.909compare.sd.N4.N5.result## paralog1 paralog2 paralog1 / paralog2
## NEW 0.01585 0.0171 0.9271
## old 0.01585 0.0171 0.9271compare.mean.N4.mikatae.result## paralog1 paralog2 paralog1 / paralog2
## NEW 0.07815 0.0808 0.9673
## old 0.07815 0.0808 0.9673compare.sd.N4.mikatae.result## paralog1 paralog2 paralog1 / paralog2
## NEW 0.02258 0.02325 0.9708
## old 0.02258 0.02325 0.9708Feb 12 update
# Now check asymmetry again using best lnL estimates from 4 tree topologies
maxlnL.PAML.omega.mean <- c(mean(geo_3.0_PAML_maxlnL_summary["omega", ]), mean(geo_10.0_PAML_maxlnL_summary["omega", ]),
mean(geo_50.0_PAML_maxlnL_summary["omega", ]), mean(geo_100.0_PAML_maxlnL_summary["omega", ]),
mean(geo_500.0_PAML_maxlnL_summary["omega", ]))
maxlnL.PAML.omega.sd <- c(sd(geo_3.0_PAML_maxlnL_summary["omega", ]), sd(geo_10.0_PAML_maxlnL_summary["omega", ]),
sd(geo_50.0_PAML_maxlnL_summary["omega", ]), sd(geo_100.0_PAML_maxlnL_summary["omega", ]),
sd(geo_500.0_PAML_maxlnL_summary["omega", ]))
plot(IGC.geo.list, maxlnL.PAML.omega.mean)
abline(h = 1.0)
plot(IGC.geo.list, maxlnL.PAML.omega.sd)
maxlnL.PAML.kappa.mean <- c(mean(geo_3.0_PAML_maxlnL_summary["kappa", ]), mean(geo_10.0_PAML_maxlnL_summary["kappa", ]),
mean(geo_50.0_PAML_maxlnL_summary["kappa", ]), mean(geo_100.0_PAML_maxlnL_summary["kappa", ]),
mean(geo_500.0_PAML_maxlnL_summary["kappa", ]))
maxlnL.PAML.kappa.sd <- c(sd(geo_3.0_PAML_maxlnL_summary["kappa", ]), sd(geo_10.0_PAML_maxlnL_summary["kappa", ]),
sd(geo_50.0_PAML_maxlnL_summary["kappa", ]), sd(geo_100.0_PAML_maxlnL_summary["kappa", ]),
sd(geo_500.0_PAML_maxlnL_summary["kappa", ]))
plot(IGC.geo.list, maxlnL.PAML.kappa.mean)
abline(h = 8.4043336)
plot(IGC.geo.list, maxlnL.PAML.kappa.sd)
Now start to look at branch length estimates
Branch lengths used in simulation:
| Branch | blen |
|---|---|
| N0_N1: | 0.0197240946542 |
| N0_kluyveri | 0.215682181791 |
| N1_N2 | 0.20925129872 |
| N1_castellii | 0.171684721483 |
| N2_N3 | 0.0257112589202 |
| N2_bayanus | 0.0266075664688 |
| N3_N4 | 0.0321083243449 |
| N3_kudriavzevii | 0.0853588718458 |
| N4_N5 | 0.024947887926 |
| N4_mikatae | 0.0566627496729 |
| N5_cerevisiae | 0.0581451177847 |
| N5_paradoxus | 0.0218788166581 |
# N0_N1
IGC.N0.N1.mean.list <- c(mean(geo_3.0_summary["(N0,N1)", ]), mean(geo_10.0_summary["(N0,N1)", ]),
mean(geo_50.0_summary["(N0,N1)", ]), mean(geo_100.0_summary["(N0,N1)", ]),
mean(geo_500.0_summary["(N0,N1)", ]))
IGC.N0.N1.sd.list <- c(sd(geo_3.0_summary["(N0,N1)", ]), sd(geo_10.0_summary["(N0,N1)", ]),
sd(geo_50.0_summary["(N0,N1)", ]), sd(geo_100.0_summary["(N0,N1)", ]),
sd(geo_500.0_summary["(N0,N1)", ]))
PAML.N0.N1.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_10.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_50.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_100.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_500.0_PAML_maxlnL_summary["N0_N1", ]))
PAML.N0.N1.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_10.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_50.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_100.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_500.0_PAML_maxlnL_summary["N0_N1", ]))
PAML.N0.N1.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_10.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_50.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_100.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_500.0_PAML_maxlnL_summary["N0_N6", ]))
PAML.N0.N1.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_10.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_50.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_100.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_500.0_PAML_maxlnL_summary["N0_N6", ]))
# N0_kluyveri
IGC.N0.kluyveri.mean.list <- c(mean(geo_3.0_summary["(N0,kluyveri)", ]), mean(geo_10.0_summary["(N0,kluyveri)", ]),
mean(geo_50.0_summary["(N0,kluyveri)", ]), mean(geo_100.0_summary["(N0,kluyveri)", ]),
mean(geo_500.0_summary["(N0,kluyveri)", ]))
IGC.N0.kluyveri.sd.list <- c(sd(geo_3.0_summary["(N0,kluyveri)", ]), sd(geo_10.0_summary["(N0,kluyveri)", ]),
sd(geo_50.0_summary["(N0,kluyveri)", ]), sd(geo_100.0_summary["(N0,kluyveri)", ]),
sd(geo_500.0_summary["(N0,kluyveri)", ]))
PAML.N0.kluyveri.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]))
PAML.N0.kluyveri.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ] ))
# N1_N2
IGC.N1.N2.mean.list <- c(mean(geo_3.0_summary["(N1,N2)", ]), mean(geo_10.0_summary["(N1,N2)", ]),
mean(geo_50.0_summary["(N1,N2)", ]), mean(geo_100.0_summary["(N1,N2)", ]),
mean(geo_500.0_summary["(N1,N2)", ]))
IGC.N1.N2.sd.list <- c(sd(geo_3.0_summary["(N1,N2)", ]), sd(geo_10.0_summary["(N1,N2)", ]),
sd(geo_50.0_summary["(N1,N2)", ]), sd(geo_100.0_summary["(N1,N2)", ]),
sd(geo_500.0_summary["(N1,N2)", ]))
PAML.N1.N2.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_10.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_50.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_100.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_500.0_PAML_maxlnL_summary["N1_N2", ]))
PAML.N1.N2.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_10.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_50.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_100.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_500.0_PAML_maxlnL_summary["N1_N2", ]))
PAML.N1.N2.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_10.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_50.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_100.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_500.0_PAML_maxlnL_summary["N6_N7", ]))
PAML.N1.N2.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_10.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_50.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_100.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_500.0_PAML_maxlnL_summary["N6_N7", ]))
# N1_castellii
IGC.N1.castellii.mean.list <- c(mean(geo_3.0_summary["(N1,castellii)", ]), mean(geo_10.0_summary["(N1,castellii)", ]),
mean(geo_50.0_summary["(N1,castellii)", ]), mean(geo_100.0_summary["(N1,castellii)", ]),
mean(geo_500.0_summary["(N1,castellii)", ]))
IGC.N1.castellii.sd.list <- c(sd(geo_3.0_summary["(N1,castellii)", ]), sd(geo_10.0_summary["(N1,castellii)", ]),
sd(geo_50.0_summary["(N1,castellii)", ]), sd(geo_100.0_summary["(N1,castellii)", ]),
sd(geo_500.0_summary["(N1,castellii)", ]))
PAML.N1.castellii.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]))
PAML.N1.castellii.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]))
PAML.N1.castellii.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]))
PAML.N1.castellii.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]))
# N2_N3
IGC.N2.N3.mean.list <- c(mean(geo_3.0_summary["(N2,N3)", ]), mean(geo_10.0_summary["(N2,N3)", ]),
mean(geo_50.0_summary["(N2,N3)", ]), mean(geo_100.0_summary["(N2,N3)", ]),
mean(geo_500.0_summary["(N2,N3)", ]))
IGC.N2.N3.sd.list <- c(sd(geo_3.0_summary["(N2,N3)", ]), sd(geo_10.0_summary["(N2,N3)", ]),
sd(geo_50.0_summary["(N2,N3)", ]), sd(geo_100.0_summary["(N2,N3)", ]),
sd(geo_500.0_summary["(N2,N3)", ]))
PAML.N2.N3.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_10.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_50.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_100.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_500.0_PAML_maxlnL_summary["N2_N3", ]))
PAML.N2.N3.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_10.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_50.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_100.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_500.0_PAML_maxlnL_summary["N2_N3", ]))
PAML.N2.N3.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_10.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_50.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_100.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_500.0_PAML_maxlnL_summary["N7_N8", ]))
PAML.N2.N3.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_10.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_50.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_100.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_500.0_PAML_maxlnL_summary["N7_N8", ]))
# N2_bayanus
IGC.N2.bayanus.mean.list <- c(mean(geo_3.0_summary["(N2,bayanus)", ]), mean(geo_10.0_summary["(N2,bayanus)", ]),
mean(geo_50.0_summary["(N2,bayanus)", ]), mean(geo_100.0_summary["(N2,bayanus)", ]),
mean(geo_500.0_summary["(N2,bayanus)", ]))
IGC.N2.bayanus.sd.list <- c(sd(geo_3.0_summary["(N2,bayanus)", ]), sd(geo_10.0_summary["(N2,bayanus)", ]),
sd(geo_50.0_summary["(N2,bayanus)", ]), sd(geo_100.0_summary["(N2,bayanus)", ]),
sd(geo_500.0_summary["(N2,bayanus)", ]))
PAML.N2.bayanus.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]))
PAML.N2.bayanus.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]))
PAML.N2.bayanus.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]))
PAML.N2.bayanus.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]))
# N3_N4
IGC.N3.N4.mean.list <- c(mean(geo_3.0_summary["(N3,N4)", ]), mean(geo_10.0_summary["(N3,N4)", ]),
mean(geo_50.0_summary["(N3,N4)", ]), mean(geo_100.0_summary["(N3,N4)", ]),
mean(geo_500.0_summary["(N3,N4)", ]))
IGC.N3.N4.sd.list <- c(sd(geo_3.0_summary["(N3,N4)", ]), sd(geo_10.0_summary["(N3,N4)", ]),
sd(geo_50.0_summary["(N3,N4)", ]), sd(geo_100.0_summary["(N3,N4)", ]),
sd(geo_500.0_summary["(N3,N4)", ]))
PAML.N3.N4.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_10.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_50.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_100.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_500.0_PAML_maxlnL_summary["N3_N4", ]))
PAML.N3.N4.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_10.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_50.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_100.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_500.0_PAML_maxlnL_summary["N3_N4", ]))
PAML.N3.N4.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_10.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_50.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_100.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_500.0_PAML_maxlnL_summary["N8_N9", ]))
PAML.N3.N4.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_10.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_50.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_100.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_500.0_PAML_maxlnL_summary["N8_N9", ]))
# N3_kudriavzevii
IGC.N3.kudriavzevii.mean.list <- c(mean(geo_3.0_summary["(N3,kudriavzevii)", ]), mean(geo_10.0_summary["(N3,kudriavzevii)", ]),
mean(geo_50.0_summary["(N3,kudriavzevii)", ]), mean(geo_100.0_summary["(N3,kudriavzevii)", ]),
mean(geo_500.0_summary["(N3,kudriavzevii)", ]))
IGC.N3.kudriavzevii.sd.list <- c(sd(geo_3.0_summary["(N3,kudriavzevii)", ]), sd(geo_10.0_summary["(N3,kudriavzevii)", ]),
sd(geo_50.0_summary["(N3,kudriavzevii)", ]), sd(geo_100.0_summary["(N3,kudriavzevii)", ]),
sd(geo_500.0_summary["(N3,kudriavzevii)", ]))
PAML.N3.kudriavzevii.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]))
PAML.N3.kudriavzevii.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]))
PAML.N3.kudriavzevii.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]))
PAML.N3.kudriavzevii.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]))
# N4_N5
IGC.N4.N5.mean.list <- c(mean(geo_3.0_summary["(N4,N5)", ]), mean(geo_10.0_summary["(N4,N5)", ]),
mean(geo_50.0_summary["(N4,N5)", ]), mean(geo_100.0_summary["(N4,N5)", ]),
mean(geo_500.0_summary["(N4,N5)", ]))
IGC.N4.N5.sd.list <- c(sd(geo_3.0_summary["(N4,N5)", ]), sd(geo_10.0_summary["(N4,N5)", ]),
sd(geo_50.0_summary["(N4,N5)", ]), sd(geo_100.0_summary["(N4,N5)", ]),
sd(geo_500.0_summary["(N4,N5)", ]))
PAML.N4.N5.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_10.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_50.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_100.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_500.0_PAML_maxlnL_summary["N4_N5", ]))
PAML.N4.N5.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_10.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_50.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_100.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_500.0_PAML_maxlnL_summary["N4_N5", ]))
PAML.N4.N5.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_10.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_50.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_100.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_500.0_PAML_maxlnL_summary["N9_N10", ]))
PAML.N4.N5.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_10.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_50.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_100.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_500.0_PAML_maxlnL_summary["N9_N10", ]))
# N4_mikatae
IGC.N4.mikatae.mean.list <- c(mean(geo_3.0_summary["(N4,mikatae)", ]), mean(geo_10.0_summary["(N4,mikatae)", ]),
mean(geo_50.0_summary["(N4,mikatae)", ]), mean(geo_100.0_summary["(N4,mikatae)", ]),
mean(geo_500.0_summary["(N4,mikatae)", ]))
IGC.N4.mikatae.sd.list <- c(sd(geo_3.0_summary["(N4,mikatae)", ]), sd(geo_10.0_summary["(N4,mikatae)", ]),
sd(geo_50.0_summary["(N4,mikatae)", ]), sd(geo_100.0_summary["(N4,mikatae)", ]),
sd(geo_500.0_summary["(N4,mikatae)", ]))
PAML.N4.mikatae.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]))
PAML.N4.mikatae.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]))
PAML.N4.mikatae.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]))
PAML.N4.mikatae.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]))
# N5_cerevisiae
IGC.N5.cerevisiae.mean.list <- c(mean(geo_3.0_summary["(N5,cerevisiae)", ]), mean(geo_10.0_summary["(N5,cerevisiae)", ]),
mean(geo_50.0_summary["(N5,cerevisiae)", ]), mean(geo_100.0_summary["(N5,cerevisiae)", ]),
mean(geo_500.0_summary["(N5,cerevisiae)", ]))
IGC.N5.cerevisiae.sd.list <- c(sd(geo_3.0_summary["(N5,cerevisiae)", ]), sd(geo_10.0_summary["(N5,cerevisiae)", ]),
sd(geo_50.0_summary["(N5,cerevisiae)", ]), sd(geo_100.0_summary["(N5,cerevisiae)", ]),
sd(geo_500.0_summary["(N5,cerevisiae)", ]))
PAML.N5.cerevisiae.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]))
PAML.N5.cerevisiae.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]))
PAML.N5.cerevisiae.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]))
PAML.N5.cerevisiae.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]))
# N5_paradoxus
IGC.N5.paradoxus.mean.list <- c(mean(geo_3.0_summary["(N5,paradoxus)", ]), mean(geo_10.0_summary["(N5,paradoxus)", ]),
mean(geo_50.0_summary["(N5,paradoxus)", ]), mean(geo_100.0_summary["(N5,paradoxus)", ]),
mean(geo_500.0_summary["(N5,paradoxus)", ]))
IGC.N5.paradoxus.sd.list <- c(sd(geo_3.0_summary["(N5,paradoxus)", ]), sd(geo_10.0_summary["(N5,paradoxus)", ]),
sd(geo_50.0_summary["(N5,paradoxus)", ]), sd(geo_100.0_summary["(N5,paradoxus)", ]),
sd(geo_500.0_summary["(N5,paradoxus)", ]))
PAML.N5.paradoxus.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]))
PAML.N5.paradoxus.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]))
PAML.N5.paradoxus.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]))
PAML.N5.paradoxus.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]))Now plot same branch length estimates from each paralog in paml results and posterior branch length from IGC + MG94 model
# N0_N1
matplot(IGC.geo.list, cbind(PAML.N0.N1.maxlnL.paralog1.mean.list, PAML.N0.N1.maxlnL.paralog2.mean.list, mean.post.N0.N1.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N0.N1 estimate")
abline(h = 0.0197240946542)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N0.N1.maxlnL.paralog1.sd.list, PAML.N0.N1.maxlnL.paralog2.sd.list, sd.post.N0.N1.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N0.N1 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N0_kluyveri
matplot(IGC.geo.list, cbind(PAML.N0.kluyveri.maxlnL.paralog1.mean.list, mean.post.N0.kluyveri.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N0.kluyveri estimate")
abline(h = 0.215682181791)
legend("right", legend = c("paralog1", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N0.kluyveri.maxlnL.paralog1.sd.list, sd.post.N0.kluyveri.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N0.kluyveri estimate")
legend("right", legend = c("paralog1", "posterior IGC"), col = 1:3, pch = 1)
# N1_N2
matplot(IGC.geo.list, cbind(PAML.N1.N2.maxlnL.paralog1.mean.list, PAML.N1.N2.maxlnL.paralog2.mean.list, mean.post.N1.N2.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N1.N2 estimate")
abline(h = 0.20925129872)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N1.N2.maxlnL.paralog1.sd.list, PAML.N1.N2.maxlnL.paralog2.sd.list, sd.post.N1.N2.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N1.N2 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N1_castellii
matplot(IGC.geo.list, cbind(PAML.N1.castellii.maxlnL.paralog1.mean.list, PAML.N1.castellii.maxlnL.paralog2.mean.list, mean.post.N1.castellii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N1.castellii estimate")
abline(h = 0.171684721483)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N1.castellii.maxlnL.paralog1.sd.list, PAML.N1.castellii.maxlnL.paralog2.sd.list, sd.post.N1.castellii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N1.castellii estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N2_N3
matplot(IGC.geo.list, cbind(PAML.N2.N3.maxlnL.paralog1.mean.list, PAML.N2.N3.maxlnL.paralog2.mean.list, mean.post.N2.N3.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N2.N3 estimate")
abline(h = 0.0257112589202)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N2.N3.maxlnL.paralog1.sd.list, PAML.N2.N3.maxlnL.paralog2.sd.list, sd.post.N2.N3.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N2.N3 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N2_bayanus
matplot(IGC.geo.list, cbind(PAML.N2.bayanus.maxlnL.paralog1.mean.list, PAML.N2.bayanus.maxlnL.paralog2.mean.list, mean.post.N2.bayanus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N2.bayanus estimate")
abline(h = 0.0266075664688)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N2.bayanus.maxlnL.paralog1.sd.list, PAML.N2.bayanus.maxlnL.paralog2.sd.list, sd.post.N2.bayanus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N2.bayanus estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N3_N4
matplot(IGC.geo.list, cbind(PAML.N3.N4.maxlnL.paralog1.mean.list, PAML.N3.N4.maxlnL.paralog2.mean.list, mean.post.N3.N4.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N3.N4 estimate")
abline(h = 0.0321083243449)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N3.N4.maxlnL.paralog1.sd.list, PAML.N3.N4.maxlnL.paralog2.sd.list, sd.post.N3.N4.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N3.N4 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N3_kudriavzevii
matplot(IGC.geo.list, cbind(PAML.N3.kudriavzevii.maxlnL.paralog1.mean.list, PAML.N3.kudriavzevii.maxlnL.paralog2.mean.list, mean.post.N3.kudriavzevii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N3.kudriavzevii estimate")
abline(h = 0.0853588718458)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N3.kudriavzevii.maxlnL.paralog1.sd.list, PAML.N3.kudriavzevii.maxlnL.paralog2.sd.list, sd.post.N3.kudriavzevii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N3.kudriavzevii estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N4_N5
matplot(IGC.geo.list, cbind(PAML.N4.N5.maxlnL.paralog1.mean.list, PAML.N4.N5.maxlnL.paralog2.mean.list, mean.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N4.N5 estimate")
abline(h = 0.024947887926)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N4.N5.maxlnL.paralog1.sd.list, PAML.N4.N5.maxlnL.paralog2.sd.list, sd.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N4.N5 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N4_mikatae
matplot(IGC.geo.list, cbind(PAML.N4.mikatae.maxlnL.paralog1.mean.list, PAML.N4.mikatae.maxlnL.paralog2.mean.list, mean.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N4.mikatae estimate")
abline(h = 0.0566627496729)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N4.mikatae.maxlnL.paralog1.sd.list, PAML.N4.mikatae.maxlnL.paralog2.sd.list, sd.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N4.mikatae estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N5_cerevisiae
matplot(IGC.geo.list, cbind(PAML.N5.cerevisiae.maxlnL.paralog1.mean.list, PAML.N5.cerevisiae.maxlnL.paralog2.mean.list, mean.post.N5.cerevisiae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N5.cerevisiae estimate")
abline(h = 0.0581451177847)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N5.cerevisiae.maxlnL.paralog1.sd.list, PAML.N5.cerevisiae.maxlnL.paralog2.sd.list, sd.post.N5.cerevisiae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N5.cerevisiae estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N5_paradoxus
matplot(IGC.geo.list, cbind(PAML.N5.paradoxus.maxlnL.paralog1.mean.list, PAML.N5.paradoxus.maxlnL.paralog2.mean.list, mean.post.N5.paradoxus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N5.paradoxus estimate")
abline(h = 0.0218788166581)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N5.paradoxus.maxlnL.paralog1.sd.list, PAML.N5.paradoxus.maxlnL.paralog2.sd.list, sd.post.N5.paradoxus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N5.paradoxus estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
Feb 10 update
# Re-examine N4_N5, N4_mikatae
IGC.geo.list <- c(3.0, 10.0, 50.0, 100.0, 500.0)
# N4_N5
non.zero.PAML.N4.N5.paralog1.mean.list <- c(mean(PAML_3.0_summary["N4_N5", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
mean(PAML_10.0_summary["N4_N5", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
mean(PAML_50.0_summary["N4_N5", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
mean(PAML_100.0_summary["N4_N5", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
mean(PAML_500.0_summary["N4_N5", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
non.zero.PAML.N4.N5.paralog1.sd.list <- c(sd(PAML_3.0_summary["N4_N5", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
sd(PAML_10.0_summary["N4_N5", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
sd(PAML_50.0_summary["N4_N5", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
sd(PAML_100.0_summary["N4_N5", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
sd(PAML_500.0_summary["N4_N5", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
non.zero.PAML.N4.N5.paralog2.mean.list <- c(mean(PAML_3.0_summary["N9_N10", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
mean(PAML_10.0_summary["N9_N10", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
mean(PAML_50.0_summary["N9_N10", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
mean(PAML_100.0_summary["N9_N10", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
mean(PAML_500.0_summary["N9_N10", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
non.zero.PAML.N4.N5.paralog2.sd.list <- c(sd(PAML_3.0_summary["N9_N10", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
sd(PAML_10.0_summary["N9_N10", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
sd(PAML_50.0_summary["N9_N10", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
sd(PAML_100.0_summary["N9_N10", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
sd(PAML_500.0_summary["N9_N10", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
# N4_mikatae
non.zero.PAML.N4.mikatae.paralog1.mean.list <- c(mean(PAML_3.0_summary["N4_mikataeYDR418W", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
mean(PAML_10.0_summary["N4_mikataeYDR418W", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
mean(PAML_50.0_summary["N4_mikataeYDR418W", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
mean(PAML_100.0_summary["N4_mikataeYDR418W", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
mean(PAML_500.0_summary["N4_mikataeYDR418W", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
non.zero.PAML.N4.mikatae.paralog1.sd.list <- c(sd(PAML_3.0_summary["N4_mikataeYDR418W", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
sd(PAML_10.0_summary["N4_mikataeYDR418W", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
sd(PAML_50.0_summary["N4_mikataeYDR418W", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
sd(PAML_100.0_summary["N4_mikataeYDR418W", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
sd(PAML_500.0_summary["N4_mikataeYDR418W", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
non.zero.PAML.N4.mikatae.paralog2.mean.list <- c(mean(PAML_3.0_summary["N9_mikataeYEL054C", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
mean(PAML_10.0_summary["N9_mikataeYEL054C", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
mean(PAML_50.0_summary["N9_mikataeYEL054C", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
mean(PAML_100.0_summary["N9_mikataeYEL054C", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
mean(PAML_500.0_summary["N9_mikataeYEL054C", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
non.zero.PAML.N4.mikatae.paralog2.sd.list <- c(sd(PAML_3.0_summary["N9_mikataeYEL054C", (PAML_3.0_summary[4, ] > 1e-5 & PAML_3.0_summary[6,] > 1e-5)]),
sd(PAML_10.0_summary["N9_mikataeYEL054C", (PAML_10.0_summary[4, ] > 1e-5 & PAML_10.0_summary[6,] > 1e-5)]),
sd(PAML_50.0_summary["N9_mikataeYEL054C", (PAML_50.0_summary[4, ] > 1e-5 & PAML_50.0_summary[6,] > 1e-5)]),
sd(PAML_100.0_summary["N9_mikataeYEL054C", (PAML_100.0_summary[4, ] > 1e-5 & PAML_100.0_summary[6,] > 1e-5)]),
sd(PAML_500.0_summary["N9_mikataeYEL054C", (PAML_500.0_summary[4, ] > 1e-5 & PAML_500.0_summary[6,] > 1e-5)]))
# N4_N5
par(mfrow = c(2, 2))
matplot(IGC.geo.list, cbind(non.zero.PAML.N4.N5.paralog1.mean.list, non.zero.PAML.N4.N5.paralog2.mean.list, mean.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean non.zero N4.N5 estimate")
abline(h = 0.024947887926)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(non.zero.PAML.N4.N5.paralog1.sd.list, non.zero.PAML.N4.N5.paralog2.sd.list, sd.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd non.zero N4.N5 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N4_N5
matplot(IGC.geo.list, cbind(PAML.N4.N5.paralog1.mean.list, PAML.N4.N5.paralog2.mean.list, mean.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N4.N5 estimate")
abline(h = 0.024947887926)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N4.N5.paralog1.sd.list, PAML.N4.N5.paralog2.sd.list, sd.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N4.N5 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
par(mfrow = c(2, 2))
# N4_mikatae
matplot(IGC.geo.list, cbind(non.zero.PAML.N4.mikatae.paralog1.mean.list, non.zero.PAML.N4.mikatae.paralog2.mean.list, mean.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean non.zero N4.mikatae estimate")
abline(h = 0.0566627496729)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(non.zero.PAML.N4.mikatae.paralog1.sd.list, non.zero.PAML.N4.mikatae.paralog2.sd.list, sd.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd non.zero N4.mikatae estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N4_mikatae
matplot(IGC.geo.list, cbind(PAML.N4.mikatae.paralog1.mean.list, PAML.N4.mikatae.paralog2.mean.list, mean.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N4.mikatae estimate")
abline(h = 0.0566627496729)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N4.mikatae.paralog1.sd.list, PAML.N4.mikatae.paralog2.sd.list, sd.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N4.mikatae estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
Feb 5 update
Check PAML estimate of two same tree topologies but different order of taxa
# Simulation using estimated Tau value of 1.409408
# Look at difference of each estimate (Tree 1 - Tree 2)
# log likelihood
summary(PAML_estimatedTau_3.0_1stTree_summary["ll", ] - PAML_estimatedTau_3.0_2ndTree_summary["ll", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0e+00 0e+00 0e+00 1e-08 0e+00 1e-06sd(PAML_estimatedTau_3.0_1stTree_summary["ll", ] - PAML_estimatedTau_3.0_2ndTree_summary["ll", ])## [1] 1e-07# kappa
summary(PAML_estimatedTau_3.0_1stTree_summary["kappa", ] - PAML_estimatedTau_3.0_2ndTree_summary["kappa", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -2e-05 0e+00 0e+00 -1e-07 0e+00 1e-05sd(PAML_estimatedTau_3.0_1stTree_summary["kappa", ] - PAML_estimatedTau_3.0_2ndTree_summary["kappa", ])## [1] 5.221e-06# omega
summary(PAML_estimatedTau_3.0_1stTree_summary["omega", ] - PAML_estimatedTau_3.0_2ndTree_summary["omega", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -1e-05 0e+00 0e+00 -3e-07 0e+00 0e+00sd(PAML_estimatedTau_3.0_1stTree_summary["omega", ] - PAML_estimatedTau_3.0_2ndTree_summary["omega", ])## [1] 1.714e-06# N0_kluyveriYDR418W
summary(PAML_estimatedTau_3.0_1stTree_summary["N0_kluyveriYDR418W", ] - PAML_estimatedTau_3.0_2ndTree_summary["N0_kluyveriYDR418W", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -5e-06 0e+00 0e+00 -1e-08 0e+00 1e-06sd(PAML_estimatedTau_3.0_1stTree_summary["N0_kluyveriYDR418W", ] - PAML_estimatedTau_3.0_2ndTree_summary["N0_kluyveriYDR418W", ])## [1] 5.773e-07# N0_N1
summary(PAML_estimatedTau_3.0_1stTree_summary["N0_N1", ] - PAML_estimatedTau_3.0_2ndTree_summary["N0_N6", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -1e-06 0e+00 0e+00 -1e-08 0e+00 0e+00sd(PAML_estimatedTau_3.0_1stTree_summary["N0_N1", ] - PAML_estimatedTau_3.0_2ndTree_summary["N0_N6", ])## [1] 1e-07There seems no difference between two different tree representations
Now check PAML results on simulation with 10*Tau
# Simulation using 10 * Tau value of 1.409408 * 10 = 14.09408
# Look at difference of each estimate (Tree 1 - Tree 2)
# log likelihood
summary(PAML_10Tau_3.0_1stTree_summary["ll", ] - PAML_10Tau_3.0_2ndTree_summary["ll", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -7.740 0.000 0.000 -0.225 0.000 5.200sd(PAML_10Tau_3.0_1stTree_summary["ll", ] - PAML_10Tau_3.0_2ndTree_summary["ll", ])## [1] 1.692hist(PAML_10Tau_3.0_1stTree_summary["ll", ] - PAML_10Tau_3.0_2ndTree_summary["ll", ])
# kappa
summary(PAML_10Tau_3.0_1stTree_summary["kappa", ] - PAML_10Tau_3.0_2ndTree_summary["kappa", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.9910 0.0000 0.0000 -0.0663 0.0000 0.1990sd(PAML_10Tau_3.0_1stTree_summary["kappa", ] - PAML_10Tau_3.0_2ndTree_summary["kappa", ])## [1] 0.1903# omega
summary(PAML_10Tau_3.0_1stTree_summary["omega", ] - PAML_10Tau_3.0_2ndTree_summary["omega", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.13200 0.00000 0.00000 -0.00004 0.00000 0.05890sd(PAML_10Tau_3.0_1stTree_summary["omega", ] - PAML_10Tau_3.0_2ndTree_summary["omega", ])## [1] 0.01823# N0_kluyveriYDR418W
summary(PAML_10Tau_3.0_1stTree_summary["N0_kluyveriYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N0_kluyveriYDR418W", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.1900 0.0000 0.0000 -0.0262 0.0000 0.0000sd(PAML_10Tau_3.0_1stTree_summary["N0_kluyveriYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N0_kluyveriYDR418W", ])## [1] 0.05796# N0_N1
summary(PAML_10Tau_3.0_1stTree_summary["N0_N1", ] - PAML_10Tau_3.0_2ndTree_summary["N0_N6", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0 0 0 0 0 0sd(PAML_10Tau_3.0_1stTree_summary["N0_N1", ] - PAML_10Tau_3.0_2ndTree_summary["N0_N6", ])## [1] 0# N1_N2
summary(PAML_10Tau_3.0_1stTree_summary["N1_N2", ] - PAML_10Tau_3.0_2ndTree_summary["N6_N7", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.3880 0.0000 0.0000 0.0036 0.0515 0.2340sd(PAML_10Tau_3.0_1stTree_summary["N1_N2", ] - PAML_10Tau_3.0_2ndTree_summary["N6_N7", ])## [1] 0.1073hist(PAML_10Tau_3.0_1stTree_summary["N1_N2", ] - PAML_10Tau_3.0_2ndTree_summary["N6_N7", ])
# N1_castelliiYDR418W
summary(PAML_10Tau_3.0_1stTree_summary["N1_castelliiYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N6_castelliiYDR418W", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.2340 -0.0515 0.0000 -0.0068 0.0000 0.3880sd(PAML_10Tau_3.0_1stTree_summary["N1_castelliiYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N6_castelliiYDR418W", ])## [1] 0.1068hist(PAML_10Tau_3.0_1stTree_summary["N1_castelliiYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N6_castelliiYDR418W", ])
# N2_N3
summary(PAML_10Tau_3.0_1stTree_summary["N2_N3", ] - PAML_10Tau_3.0_2ndTree_summary["N7_N8", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.07610 -0.01730 0.00000 -0.00754 0.00000 0.05470sd(PAML_10Tau_3.0_1stTree_summary["N2_N3", ] - PAML_10Tau_3.0_2ndTree_summary["N7_N8", ])## [1] 0.02132hist(PAML_10Tau_3.0_1stTree_summary["N2_N3", ] - PAML_10Tau_3.0_2ndTree_summary["N7_N8", ])
# N2_N3
summary(PAML_10Tau_3.0_1stTree_summary["N2_N3", ] - PAML_10Tau_3.0_2ndTree_summary["N7_N8", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.07610 -0.01730 0.00000 -0.00754 0.00000 0.05470sd(PAML_10Tau_3.0_1stTree_summary["N2_N3", ] - PAML_10Tau_3.0_2ndTree_summary["N7_N8", ])## [1] 0.02132hist(PAML_10Tau_3.0_1stTree_summary["N2_N3", ] - PAML_10Tau_3.0_2ndTree_summary["N7_N8", ])
# N2_bayanusYDR418W
summary(PAML_10Tau_3.0_1stTree_summary["N2_bayanusYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N7_bayanusYDR418W", ])## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.05470 -0.00004 0.00000 0.00712 0.01730 0.07610sd(PAML_10Tau_3.0_1stTree_summary["N2_bayanusYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N7_bayanusYDR418W", ])## [1] 0.0208hist(PAML_10Tau_3.0_1stTree_summary["N2_bayanusYDR418W", ] - PAML_10Tau_3.0_2ndTree_summary["N7_bayanusYDR418W", ])
Now start to check branches ratio of subtree branches of paralog 1 over paralog 2 ratios
# N0_N1
target <- PAML_3.0_summary["N0_N1", ] / PAML_3.0_summary["N0_N6", ]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 682.6## [1] 1311# N1_N2
target <- PAML_3.0_summary["N1_N2", ] / PAML_3.0_summary["N6_N7", ]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.009## [1] 0.2219# N1_castellii
target <- PAML_3.0_summary["N1_castelliiYDR418W", ] / PAML_3.0_summary["N6_castelliiYEL054C", ]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.01## [1] 0.2422# N2_N3
target <- PAML_3.0_summary["N2_N3", ] / PAML_3.0_summary["N7_N8", ]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 396.5## [1] 1982# N2_bayanus
target <- PAML_3.0_summary["N2_bayanusYDR418W", ] / PAML_3.0_summary["N7_bayanusYEL054C", ]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.136## [1] 0.6685# N3_N4
target <- PAML_3.0_summary["N3_N4", ] / PAML_3.0_summary["N8_N9", ]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 1.501## [1] 1.811# N3_kudriavzevii
target <- PAML_3.0_summary["N3_kudriavzeviiYDR418W", ] / PAML_3.0_summary["N8_kudriavzeviiYEL054C", ]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.04## [1] 0.329# N4_N5
target <- PAML_3.0_summary["N4_N5", ] / PAML_3.0_summary["N9_N10", ]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 0.9776## [1] 1.313# N4_mikatae
target <- PAML_3.0_summary["N4_mikataeYDR418W", ] / PAML_3.0_summary["N9_mikataeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 1.867## [1] 1.964# N5_paradoxus
target <- PAML_3.0_summary["N5_paradoxusYDR418W", ] / PAML_3.0_summary["N10_paradoxusYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 1.377## [1] 1.532# N5_cerevisiae
target <- PAML_3.0_summary["N5_cerevisiaeYDR418W", ] / PAML_3.0_summary["N10_cerevisiaeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.042## [1] 0.502# N0_N1
target <- PAML_10.0_summary["N0_N1", ] / PAML_10.0_summary["N0_N6", ]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 808.2## [1] 1663# N1_N2
target <- PAML_10.0_summary["N1_N2", ] / PAML_10.0_summary["N6_N7", ]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.071## [1] 0.2817# N1_castellii
target <- PAML_10.0_summary["N1_castelliiYDR418W", ] / PAML_10.0_summary["N6_castelliiYEL054C", ]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.026## [1] 0.3345# N2_N3
target <- PAML_10.0_summary["N2_N3", ] / PAML_10.0_summary["N7_N8", ]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 161.1## [1] 1169# N2_bayanus
target <- PAML_10.0_summary["N2_bayanusYDR418W", ] / PAML_10.0_summary["N7_bayanusYEL054C", ]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 32.6## [1] 314# N3_N4
target <- PAML_10.0_summary["N3_N4", ] / PAML_10.0_summary["N8_N9", ]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 1.538## [1] 1.69# N3_kudriavzevii
target <- PAML_10.0_summary["N3_kudriavzeviiYDR418W", ] / PAML_10.0_summary["N8_kudriavzeviiYEL054C", ]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.144## [1] 0.4798# N4_N5
target <- PAML_10.0_summary["N4_N5", ] / PAML_10.0_summary["N9_N10", ]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 211## [1] 1482# N4_mikatae
target <- PAML_10.0_summary["N4_mikataeYDR418W", ] / PAML_10.0_summary["N9_mikataeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 113.2## [1] 1109# N5_paradoxus
target <- PAML_10.0_summary["N5_paradoxusYDR418W", ] / PAML_10.0_summary["N10_paradoxusYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 1.291## [1] 1.113# N5_cerevisiae
target <- PAML_10.0_summary["N5_cerevisiaeYDR418W", ] / PAML_10.0_summary["N10_cerevisiaeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.041## [1] 0.5688# N0_N1
target <- PAML_50.0_summary["N0_N1", ] / PAML_50.0_summary["N0_N6", ]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 544## [1] 1427# N1_N2
target <- PAML_50.0_summary["N1_N2", ] / PAML_50.0_summary["N6_N7", ]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.073## [1] 0.2958# N1_castellii
target <- PAML_50.0_summary["N1_castelliiYDR418W", ] / PAML_50.0_summary["N6_castelliiYEL054C", ]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.021## [1] 0.2728# N2_N3
target <- PAML_50.0_summary["N2_N3", ] / PAML_50.0_summary["N7_N8", ]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 1.352## [1] 1.576# N2_bayanus
target <- PAML_50.0_summary["N2_bayanusYDR418W", ] / PAML_50.0_summary["N7_bayanusYEL054C", ]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.46## [1] 1.934# N3_N4
target <- PAML_50.0_summary["N3_N4", ] / PAML_50.0_summary["N8_N9", ]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 43.96## [1] 424.1# N3_kudriavzevii
target <- PAML_50.0_summary["N3_kudriavzeviiYDR418W", ] / PAML_50.0_summary["N8_kudriavzeviiYEL054C", ]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.166## [1] 0.7124# N4_N5
target <- PAML_50.0_summary["N4_N5", ] / PAML_50.0_summary["N9_N10", ]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 1.407## [1] 1.702# N4_mikatae
target <- PAML_50.0_summary["N4_mikataeYDR418W", ] / PAML_50.0_summary["N9_mikataeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 186.1## [1] 1843# N5_paradoxus
target <- PAML_50.0_summary["N5_paradoxusYDR418W", ] / PAML_50.0_summary["N10_paradoxusYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 101.7## [1] 572.2# N5_cerevisiae
target <- PAML_50.0_summary["N5_cerevisiaeYDR418W", ] / PAML_50.0_summary["N10_cerevisiaeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.336## [1] 0.9247# N0_N1
target <- PAML_100.0_summary["N0_N1", ] / PAML_100.0_summary["N0_N6", ]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 702.9## [1] 1764# N1_N2
target <- PAML_100.0_summary["N1_N2", ] / PAML_100.0_summary["N6_N7", ]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.05## [1] 0.3782# N1_castellii
target <- PAML_100.0_summary["N1_castelliiYDR418W", ] / PAML_100.0_summary["N6_castelliiYEL054C", ]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.032## [1] 0.2839# N2_N3
target <- PAML_100.0_summary["N2_N3", ] / PAML_100.0_summary["N7_N8", ]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 89.56## [1] 539.4# N2_bayanus
target <- PAML_100.0_summary["N2_bayanusYDR418W", ] / PAML_100.0_summary["N7_bayanusYEL054C", ]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.386## [1] 1.511# N3_N4
target <- PAML_100.0_summary["N3_N4", ] / PAML_100.0_summary["N8_N9", ]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 888.6## [1] 5071# N3_kudriavzevii
target <- PAML_100.0_summary["N3_kudriavzeviiYDR418W", ] / PAML_100.0_summary["N8_kudriavzeviiYEL054C", ]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.238## [1] 0.9739# N4_N5
target <- PAML_100.0_summary["N4_N5", ] / PAML_100.0_summary["N9_N10", ]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 1.446## [1] 3.041# N4_mikatae
target <- PAML_100.0_summary["N4_mikataeYDR418W", ] / PAML_100.0_summary["N9_mikataeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 2.462## [1] 3.709# N5_paradoxus
target <- PAML_100.0_summary["N5_paradoxusYDR418W", ] / PAML_100.0_summary["N10_paradoxusYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 845.1## [1] 7179# N5_cerevisiae
target <- PAML_100.0_summary["N5_cerevisiaeYDR418W", ] / PAML_100.0_summary["N10_cerevisiaeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.472## [1] 1.873# N0_N1
target <- PAML_500.0_summary["N0_N1", ] / PAML_500.0_summary["N0_N6", ]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 390.8## [1] 1293# N1_N2
target <- PAML_500.0_summary["N1_N2", ] / PAML_500.0_summary["N6_N7", ]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1219## [1] 8571# N1_castellii
target <- PAML_500.0_summary["N1_castelliiYDR418W", ] / PAML_500.0_summary["N6_castelliiYEL054C", ]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.067## [1] 0.2985# N2_N3
target <- PAML_500.0_summary["N2_N3", ] / PAML_500.0_summary["N7_N8", ]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 1309## [1] 6196# N2_bayanus
target <- PAML_500.0_summary["N2_bayanusYDR418W", ] / PAML_500.0_summary["N7_bayanusYEL054C", ]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 547.7## [1] 4709# N3_N4
target <- PAML_500.0_summary["N3_N4", ] / PAML_500.0_summary["N8_N9", ]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 605.8## [1] 2710# N3_kudriavzevii
target <- PAML_500.0_summary["N3_kudriavzeviiYDR418W", ] / PAML_500.0_summary["N8_kudriavzeviiYEL054C", ]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.347## [1] 1.256# N4_N5
target <- PAML_500.0_summary["N4_N5", ] / PAML_500.0_summary["N9_N10", ]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 1018## [1] 9689# N4_mikatae
target <- PAML_500.0_summary["N4_mikataeYDR418W", ] / PAML_500.0_summary["N9_mikataeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 722.6## [1] 3206# N5_paradoxus
target <- PAML_500.0_summary["N5_paradoxusYDR418W", ] / PAML_500.0_summary["N10_paradoxusYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 140.7## [1] 824.2# N5_cerevisiae
target <- PAML_500.0_summary["N5_cerevisiaeYDR418W", ] / PAML_500.0_summary["N10_cerevisiaeYEL054C", ] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.353## [1] 1.52